Discussion on Competition for Spatial Statistics for Large Datasets

Research output: Contribution to journalReview articlepeer-review

Abstract

The team of Tohoku University attended sub-competition 2b in the competition on spatial statistics for large datasets, where prediction on 100,000 testing points were to be constructed conditional on 900,000 training points. We chose a covariance tapering approach in a simplified way to manage one million spatial data points. Dividing [ 0 , 1 ] 2 into 30 × 30 sub-regions with equal area, we construct predictors separately in each sub-region conditional on training data over the extended sub-region with length enlarged by 2 by fitting Matérn class covariances.

Original languageEnglish
JournalJournal of Agricultural, Biological, and Environmental Statistics
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Covariance tapering
  • Cross validation
  • Matern class

ASJC Scopus subject areas

  • Statistics and Probability
  • Environmental Science(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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